The power costs to operate a typical desktop computer and monitor often averages between $50-$75 per year, depending on factors such as usage and configuration. In some instances, power consumption in advanced CPU processing systems such as on computer server farms can be as high as $100 per year per unit. For an organization operating thousands of machines across multiple locations, these monthly energy costs can quickly add up to hundreds of thousands of dollars.
IT departments have known for some time that by analyzing usage patterns and managing the power state of the components inside a PC energy usage can be controlled. For example, the following elements of a typical PC can be individually and actively controlled to reduce power consumption: CPU(s); monitor; hard drives; USB ports; and PCI buses. Further, IT department personnel have known that power consumption in a computing environment is real, and needs to be controlled. For example, recently Google, Microsoft, and others have located computer server farms in northern climates such as Finland and Canada to reduce the cost and complexity of cooling their computing facilities. And, while heat created by PCs in the general workplace environment may not be as dramatic as in high performance server farms, the power consumption is still real and substantial power savings can be realized by organizations. Moreover, organizations are increasingly conscious of the depth of carbon footprints created by their activates and reduction efforts are ongoing as part of the “green revolution.”
The problem is that such management can be time consuming for IT departments because each organization typically has many variants of PCs, laptops, tablet PCs, and other computing devices, and each model variant must have its own tailored power scheme to reduce power consumption, and that scheme must also be customized in a manner that is compatible with the computing demands of that device within the organization. Further, IT departments typically do not even address the power consumption reduction strategies because they do not know if such additional effort would result in substantive savings to the organization, or if such savings will outweigh the cost of the additional IT personnel man hours required to configure each computing device.
Therefore, what is needed is a process for easily establishing an accurate cost savings expectation for an enterprise computing topology if power consumption protocols are established, and then deploying power schemes across the computing environment in response to such cost savings quantification.